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Genetics (MEG) Lab led by Johannes Cairns at the Department of Experimental Medical Science, Faculty of Medicine, Lund University. The group studies microbial evolution, antimicrobial resistance and
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Perspectives of Science BIOL 215 Introduction to Ecology & Evolution BIOL 219 Introduction to Physical Biology of the Cell BIOL 301 Cell and Molecular Laboratory BIOL 302 Fundamentals of Genetics and Genomics
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candidates interested in understanding the origin and evolution of habitable environments on terrestrial planets through theoretical, computational, and interdisciplinary approaches. Our research
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into account geomorphological glacier conditions and local climate, that will finally make estimates of future glacier evolution more robust and spatially coherent. Where to apply Website https
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Department of Biological and Environmental Sciences, University of Gothenburg | Sweden | about 1 month ago
measures to mitigate and adapt to these changes. This position is particularly linked to the BECC grand challenges “Biodiversity under Global Change” and “Ecosystem Services under Global Change” ( https
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, Ecology & Evolutionary Biology Posting Number req26894 Department Ecology & Evolutionary Biology Department Website Link https://eeb.arizona.edu/ Location Tucson Campus Address Tucson, AZ USA Position
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studying habitability for life as we know it based on fundamental physio-geo-chemical processes set by the planet’s evolution. The study of planetary habitability in this SFB is therefore oriented
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Universidad Andrés Bello | about 2 months ago
projects in astrophysics. Main research topics carried out by the Astrophysics Group are exoplanets, protoplanetary disks, stellar evolution and populations, Milky Way, globular clusters, gaseous
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UT Austin Home Open Rank Search in Plant Evolution and Director of the UT-Austin Plant Resources Center Apply now Description The Department of Integrative Biology at the University of Texas at
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, their photoluminescence properties have been less thoroughly explored. In this context, the AI-Unclon project funded by the ANR aims to use machine learning tools to predict the evolution of